Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging

Abstract

Forgery and tampering continue to provide unnecessary economic burdens. Although new anti-forgery and counterfeiting technologies arise, they inadvertently lead to the sophistication of forgery techniques over time, to a point where detection is no longer viable without technological aid. Among the various optical techniques, one of the recently used techniques to detect counterfeit products is HSI, which captures a range of electromagnetic data. To aid in the further exploration and eventual application of the technique, this study categorizes and summarizes existing related studies on hyperspectral imaging and creates a mini meta-analysis of this stream of literature. The literature review has been classified based on the product HSI has used in counterfeit documents, photos, holograms, artwork, and currency detection.

Robust Optical Physical Unclonable Function Based on Total Internal Reflection for Portable Authentication

“…Counterfeiting is an increasing concern in a variety of industries including electronics, security, pharmaceuticals, and cosmetics. − Counterfeit goods not only pose significant threats to consumer health and safety but also inflict severe damage on brand reputation and corporate profits. Watermarks, holographic designs, graphical barcodes, specialized inks, and RFID tags are common anticounterfeiting methods employed by manufacturers on packaging. However, these anticounterfeiting methods are susceptible to replication due to predictable manufacturing processes. , …”

Automatic Counterfeit Currency Detection Using a Novel Snapshot Hyperspectral Imaging Algorithm

“…HSI acquires the spectrum for each pixel in an image [ 18 , 19 , 20 , 21 ]. It has been used in many applications, such as cancer detection [ 22 , 23 , 24 , 25 ], air pollution monitoring [ 26 , 27 ], nanostructure identification [ 28 , 29 , 30 , 31 ], aerospace [ 32 , 33 , 34 ], food quality maintenance [ 35 ], verification [ 36 , 37 , 38 ], military [ 39 ], remote sensing [ 40 , 41 , 42 ], and agriculture [ 43 ].…”

Early esophageal detection using hyperspectral engineering and convolutional neural network

“…The use of hyperspectral imaging (HSI) technology in conjunction with artificial intelligence (AI) deep learning (DL) techniques for the analysis of spectral data pertaining to esophageal cancer (EC) has the potential to enhance the efficiency and precision of diagnostic procedures [5]. Hyperspectral pictures possess spectral intervals at the nanoscale level, resulting in a much greater capacity to detect spectrum information compared to multispectral images [6][7][8][9]. Spectrum conversion refers to the application of an imaging spectrometer to capture a picture including a broad range of wavelengths [10,11].…”